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Likelier
Crime · reviewed 2026-05-25

What are the odds your bicycle gets stolen?

Evidence quality 4.63/5

Eight-dimension review score against the quality rubric . Each dimension scored 1–5.

D1 Source grounding
5/5
D2 Source authority
5/5
D3 Arithmetic
4/5
D4 Uncertainty
4/5
D5 Scope
4/5
D6 Prose
5/5
D7 Perception honesty
5/5
D8 Caveat completeness
5/5
Average 4.63/5
Direct evidence

Lifetime probability · lifetime, US adult

1 in 2.9

34% lifetime chance

range 1 in 5.0 to 1 in 2.0

lifetime, US adult each band = 10× rarer → See full scale →
certain 1 in 1K 1 in 1M 1 in 1B

≈ As likely as

An empty bicycle rack on a city sidewalk with a single cut cable lock looped through it, flat vector illustration in muted tones.

Perceived

Cyclists' intuition is shaped by stories — the lifted U-lock from outside the library, the second-hand bike that turned up on Craigslist a week later, the friend who switched to a $90 commuter after their good road bike disappeared. The headline number is hard to pin down because police data captures only a fraction of what happens, and most cyclists rely on lived experience: "give it enough years and somebody will get you." That instinct is closer to right than wrong. Across a typical US adult lifetime — most of which includes some period of bike ownership — at least one stolen bicycle is more likely than not for committed cyclists, and roughly a coin-flip across all adults.

Rough estimate: ~1 in 3 over a US adult lifetime; higher among regular cyclists

Source: editorial intuition, not polled

Actual

~710 stolen adult bicycles per 100,000 US adults per year (2024 estimate)

US adults

Show derivation

Agarwal et al. (2025), a peer-reviewed YouGov-weighted survey of 1,748 US adults plus a 430-cyclist booster, estimate roughly 2.4 million adult bicycles are stolen in the United States each year — a population rate of about 709.6 per 100,000 adults per year. Naive compounding over a 59-year adult life-horizon, treating each year as an independent trial at the population rate, gives 1 − (1 − 0.0071)^59 ≈ 0.343. This is a per-US-adult lifetime probability, not a per-owner figure: it bakes in the fact that not every adult owns a bike, and not every owner owns one continuously. Among regular cyclists the figure is substantially higher — Agarwal et al.'s cyclist booster sub-sample reports materially elevated annual victimization rates, and the UK Crime Survey for England and Wales has long shown about 2% of bicycle-owning households are hit per year, which compounds to roughly 1 − 0.98^59 ≈ 70% over an adult lifetime of continuous bike ownership. The repeat-victimization rate in bicycle theft is well-documented (a small fraction of people get hit multiple times), which nudges the unique-victim estimate downward relative to the naive compound. Uncertainty is wide because the survey is the first large modern US estimate and supersedes a frequently-cited but methodologically thin "1.5 million per year" NCVS extrapolation from a 2008 COPS guide.

Caveats: The 34% headline is a population-average lifetime probability — it mixes bike-ow…

The 34% headline is a population-average lifetime probability — it mixes bike-owning adults with non-owners. Among committed cyclists who own and ride a bike continuously for decades, the lifetime probability of at least one theft is much higher; Agarwal et al.'s cyclist booster sub-sample reports materially elevated annual rates, and the UK CSEW per-owning-household figure compounds to roughly 70% over 59 years of continuous ownership. The bicycle theft rate also varies enormously by city density, lock quality, and parking location, but the academic literature is qualitative on these multipliers — Sidebottom et al. (2009) note that cyclists are about three times more likely to have a bicycle stolen than car owners are to have their car stolen, and the COPS guide stresses that "secure" locks are those that resist hand-tool attack for at least three minutes, but there is no peer-reviewed relative-risk study quantifying a U-lock vs cable-lock multiplier. The COPS guide does state that "most stolen bicycles, regardless of theft location, are either not locked at all or are secured using a lock that requires little force to break or remove" — meaning unlocked and cable-locked bikes dominate the victim pool — but this is a share-of-stolen-bikes statistic, not a per-bike-night rate ratio, and cannot be converted into a clean "left unlocked outside the cafe" multiplier without an exposure denominator (what fraction of cyclist parking events are unsecured) that no published study reports. The most consistent finding across the literature is counter-intuitive: bicycles are more often stolen from residential premises, garages and sheds than from public racks, partly because public-rack exposure is intermittent while at-home exposure is continuous. Agarwal et al. also find that lower-income households and several non-white racial groups in the US experience significantly higher theft rates; exact multipliers are in the paper's tables and are not reproduced here. The economic value of an individual theft is modest — median bike value in Agarwal's sample is $374.50 — which is why so few thefts get reported.

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Compare to:

In the United States, roughly 2.4 million adult bicycles are stolen each year, according to a peer-reviewed YouGov-weighted survey published in Findings in January 2025 — a rate of about 710 per 100,000 US adults per year. Compounded naively over a 59-year adult life-horizon, that gives a lifetime probability of around 1 in 3 that an adult experiences at least one stolen bicycle. That headline averages over the entire adult population, including the half who never own a bike. Filter to people who actually own and ride a bike for years at a stretch and the figure climbs substantially — the UK Crime Survey has reported about 2% of bicycle-owning households victimised per year since the mid-2010s, which compounds to roughly 70% over a full adult life of continuous ownership. The instinct that “give it enough years and somebody will get you” is, for committed cyclists, well-calibrated.

The official numbers undercount dramatically. The FBI’s NIBRS pipeline counted about 128,000 bicycle thefts reported to police in 2023; the Agarwal et al. survey implies the true total is roughly twenty times higher. The 2008 COPS Office guide on bicycle theft put the cross-country average reporting rate at 56%, but the US figure now appears closer to 7%. Most stolen bicycles are too individually low-value to motivate a police report — Agarwal et al. peg the median bike’s value at about $375 — and many are insured under household contents policies where the deductible exceeds the bike’s worth. This means the visible side of bicycle crime, the bit that shows up in crime dashboards and annual UCR press releases, is a small and not-necessarily-representative fraction of the actual victim pool.

Where bicycles get stolen runs counter to the public-rack mental image. The COPS guide notes that most bicycles reported stolen “are taken from on or near the premises of the victim’s home (including garages and sheds), or from outside of shops or recreational facilities” — the modal scene is a garage or back yard, not a busy public stand. The bike-rack-outside-the-library archetype shows up disproportionately in news coverage because the bikes there are higher-value and the cyclists more vocal, not because that location is the biggest source of incidents. Lock quality matters, but the academic literature is qualitative: Sidebottom and colleagues’ 2009 European Journal of Criminology paper finds cyclists are about three times more likely to have a bike stolen than car owners are to have their car stolen, and the COPS guide defines a “secure” lock as one that withstands a three-minute hand-tool attack, but there is no peer-reviewed relative-risk study quantifying a U-lock vs cable-lock multiplier. The honest summary: bicycle theft is common, mostly invisible to the official statistics, and dominated by opportunistic theft from the places cyclists assume are safe.

Claim ledger

Every number below is what each source reported, with the verbatim quote we relied on and how we arrived at our figure. Click any link to verify directly.

  1. [1] Findings (peer-reviewed open-access transport journal) — Bicycle Theft in the US: Magnitude and Equity Impacts
    Bicycle Theft in the US: Magnitude and Equity Impacts
    Statistic
    About 2.4 million adult bicycles are stolen annually in the US, a rate of 709.6 per 100,000 people per year. The annual value of adult bicycle theft is about $1.4 billion. In 2019, about 157,669 bicycles were reported stolen to law enforcement — implying roughly 93% of incidents go unreported.
    Excerpt
    “"About 2.4 million adult bicycles are stolen annually in the US, a rate of 709.6 per 100,000 people per year. The annual value of adult bicycle theft is about $1.4 billion. In 2019, about 157,669 bicycles were reported stolen to law enforcement in the United States." ”
    Source data from
    2025-01-16
    Accessed
    2026-05-25 · archived copy
    Calculation
    The 709.6/100,000/year is the headline annual rate per all US adults (denominator includes non-owners). For the normalized lifetime figure we treat each adult-year as an independent trial at that rate and compound over a 59-year horizon: 1 − (1 − 0.00710)^59 ≈ 0.343. The 2.4 million annual total comes from Agarwal et al.'s YouGov-weighted survey (n = 1,748 general population + 430 active cyclist booster, March 2024), with weighting to match US adult demographics on gender, age, race, education, and region. The implied underreporting ratio (2.4M survey vs 157,669 police-reported in 2019) is about 15:1 — far higher than the ~2:1 NCVS-vs-UCR ratio for burglary, partly because most stolen bikes are individually too low-value to motivate filing a police report.
    Independence
    This is the primary survey source; cross-checked against Bike Index's registry-based theft counts (which align directionally with the survey's growth claim) and the FBI Crime Data Explorer NIBRS figure (~127,646 reported in 2023) as a lower bound.
  2. [2] US Department of Justice, Office of Community Oriented Policing Services; authored by Shane D. Johnson, Aiden Sidebottom, and Adam Thorpe — Bicycle Theft (Problem-Oriented Guide for Police No. 52)
    Bicycle Theft (Problem-Oriented Guide for Police No. 52)
    Statistic
    Across 17 countries surveyed (including the United States), on average only 56 percent of bicycle thefts were reported to the police; most bicycles reported stolen are taken from on or near the premises of the victim's home (including garages and sheds), or from outside of shops or recreational facilities.
    Excerpt
    “"Across the 17 countries surveyed (including the United States), on average only 56 percent of bicycle thefts were reported to the police. … Most bicycles reported stolen are taken from on or near the premises of the victim's home (including garages and sheds), or from outside of shops or recreational facilities." ”
    Source data from
    2008-01-01
    Accessed
    2026-05-25 · archived copy
    Calculation
    Used for the qualitative framing of where thefts happen (counter-intuitively, the residential premises and garage are the modal location rather than the public rack) and as supporting evidence for the underreporting story. The 56% reporting rate in this guide is an international cross-country average; the Agarwal 2025 US-specific figure is much lower (~7% reported, or 93% unreported) and supersedes it for the US headline. The 2004 US figure cited in the guide ("more than 250,000 bicycles stolen each year" based on NCVS) is also superseded by Agarwal 2025.
    Independence
    DOJ COPS Office is an independent law-enforcement-research arm; the authors are UK-based academic criminologists (UCL Jill Dando Institute) writing under US federal grant. Independent of the Agarwal 2025 transport-research pipeline.
  3. [3] Office for National Statistics (UK), Crime Survey for England and Wales — Overview of bicycle theft in England and Wales
    Overview of bicycle theft in England and Wales
    Statistic
    Around 2 in 100 bicycle-owning households in England and Wales were victims of bicycle theft in the previous 12 months; this is roughly one-third of the 1995 peak of 6 in 100.
    Excerpt
    “"Around 2 in 100 bicycle-owning households have been victims of bicycle theft in the previous 12 months … this is around a third of the rate in the 1995 peak of around 6 in 100 households. The Crime Survey for England and Wales has collected information on bicycle theft in a consistent manner since the survey first ran in 1981." ”
    Source data from
    2017-07-20
    Accessed
    2026-05-25 · archived copy
    Calculation
    International cross-check anchor. 2% per bicycle-owning household per year compounds to 1 − 0.98^59 ≈ 0.70 over an adult lifetime of continuous bike ownership, which is consistent with the much higher per-owner rate implied by Agarwal 2025 once non-owners are filtered out of the denominator. The UK Crime Survey is a long-running household victimization survey directly comparable in methodology to the US NCVS but with explicit bicycle-theft tabulation that NCVS lacks.
    Independence
    ONS is the UK's independent national statistics agency. CSEW methodology is fully independent of both Agarwal 2025 (US YouGov panel) and the COPS 2008 guide (US police-data review).

412 risks with measured probability
1 in 10 1 in 100 1 in 1K 1 in 10K 1 in 100K 1 in 1M 1 in 10M 1 in 100M 1 in 1B certain rarer → Cosmetic surgery abroad risk — 1 in 10 Infant sugar/salt and adult disease — 1 in 10 Endometriosis — 1 in 10 Hair transplant Turkey risk — 1 in 10 Knee replacement — 1 in 10 Chronic painkillers — 1 in 10 Elderly abandonment — 1 in 9.1 Complete tooth loss — 1 in 9.1 Alzheimer's — 1 in 8.3 Sleep deprivation — 1 in 8.3 Smokeless tobacco — 1 in 8.3 Cycling w/o helmet — 1 in 8.0 Bruxism tooth damage — 1 in 7.7 Vision loss — 1 in 6.7 Hernia from lifting — 1 in 6.7 Hip fracture risk — 1 in 6.7 Regular drinking — 1 in 6.7 First heart attack — 1 in 5.9 Infertility — 1 in 5.7 5+ years paid LTC — 1 in 5.6 CTE (football) — 1 in 5.0 Major depression — 1 in 4.9 Hiking injury — 1 in 4.8 Infection from sharing food with child — 1 in 4.2 Lyme disease — 1 in 4.0 Loneliness & health — 1 in 3.8 Job loss & depression — 1 in 3.7 Inheriting AUD risk — 1 in 3.5 Alcohol use disorder — 1 in 3.4 Menopause CV risk acceleration — 1 in 3.0 Silent diabetes — 1 in 3.0 Flying with cold — 1 in 2.9 Tick illness (forest) — 1 in 2.9 Silent high cholesterol — 1 in 2.9 Grandparent loss in childhood — 1 in 2.8 Pacifier floor drop — 1 in 2.8 Drug-resistant infection — 1 in 2.6 No marrow match — 1 in 2.4 Nursing home admission — 1 in 2.2 Skipping dental checkups — 1 in 2.1 False-positive mammogram — 1 in 2.0 Regular smoking — 1 in 2.0 Travelers' diarrhea — 1 in 2.0 Adventure sports — 1 in 1.8 Family caregiver probability — 1 in 1.8 LTC need after 65 — 1 in 1.8 Widowhood probability — 1 in 1.7 Unprotected sex — 1 in 1.5 Silent hypertension — 1 in 1.3 Chronic back pain — 1 in 1.3 Hand hygiene — 1 in 1.0 Cancer (any) — 1 in 7.1 E-scooter no helmet — 1 in 4.5 E-bike no helmet — 1 in 4.0 Mishandled luggage — 1 in 3.7 Deer collision — 1 in 2.7 At-fault injury crash — 1 in 2.5 Flight cancellation — 1 in 1.8 Trip disruption: war or disaster — 1 in 1.7 Home burglary (global) — 1 in 9.1 Hitchhiking assault — 1 in 8.8 Mail check fraud — 1 in 7.7 Child sexual abuse — 1 in 6.8 Stalking — 1 in 6.2 Student sexual assault — 1 in 5.7 Domestic violence — 1 in 3.7 Night walk assault — 1 in 3.6 Bicycle theft — 1 in 2.9 Sexual assault — 1 in 2.9 Home burglary — 1 in 2.6 Sexual harassment (lifetime) — 1 in 1.6 Water scarcity — 1 in 2.5 Carrington-class solar storm — 1 in 1.9 WAIS tipping point — 1 in 1.1 Indoor cat escape harm — 1 in 10 Off-leash dog bite — 1 in 8.9 Rabbit dies in 4 years — 1 in 3.3 Dog bite (non-fatal) — 1 in 1.8 Hamster dies before teenager — 1 in 1.0 Vitamin D gap — 1 in 2.9 Undercooked food — 1 in 1.6 Raw meat cross-contamination — 1 in 1.4 Food left out — 1 in 1.2 AI voice scam — 1 in 2.9 Online scam loss — 1 in 2.5 Teen cyberbullying — 1 in 2.0 Kids & explicit content — 1 in 1.9 Data breach — 1 in 1.1 Miscarriage — 1 in 6.7 Teen suicide attempt — 1 in 5.6 Postpartum depression — 1 in 4.8 Painkiller before infant vaccination — 1 in 3.8 Excessive pregnancy weight — 1 in 2.6 Unvaxxed child & measles — 1 in 2.0 Elder fraud loss — 1 in 10 Pension fund collapse — 1 in 10 Personal bankruptcy — 1 in 10 Housing crash — 1 in 8.3 Crypto total loss — 1 in 6.7 IRS audit — 1 in 6.7 Visa overstay deportation — 1 in 5.6 Long term disability working age — 1 in 4.0 Student loan default — 1 in 3.8 Whistleblower retaliation — 1 in 3.2 Career obsolescence — 1 in 2.9 Forced job exit before retirement — 1 in 2.9 Retirement shortfall — 1 in 2.6 Divorce — 1 in 2.4 Burst pipe damage — 1 in 2.2 Workplace bullying — 1 in 2.1 Deportation (undocumented) — 1 in 1.8 Funeral cost shock — 1 in 1.8 Identity theft — 1 in 1.7 Credit card fraud — 1 in 1.5 School bullying — 1 in 1.5 Insurance claim denial — 1 in 1.4 Frontline soldier casualty — 1 in 1.3 Economic recession — 1 in 1.0 Stock market crash — 1 in 1.0 Hail roof damage — 1 in 3.0 Dry toilet paper harm — 1 in 100 Secondhand smoke — 1 in 91 Gaming disorder (adults) — 1 in 83 High-heel ER visit — 1 in 79 Child throwing object — 1 in 67 Medication reaction — 1 in 58 Cat litter toxoplasmosis — 1 in 48 Mental health LTD claim — 1 in 45 Drug overdose — 1 in 42 Benzo dependence — 1 in 40 Tap water lead — 1 in 40 Medication misuse — 1 in 35 Traumatic brain injury — 1 in 33 Hospital infection — 1 in 31 Air pollution — 1 in 29 End-stage kidney disease — 1 in 29 Traveler's diarrhea (water) — 1 in 26 Skiing injury — 1 in 26 Bipolar disorder — 1 in 23 Dental tourism complication — 1 in 20 Pet parasites — 1 in 20 Undiagnosed ADHD — 1 in 20 Adult-onset food allergy — 1 in 19 Indoor cooking smoke — 1 in 18 Non-Alzheimer's dementia — 1 in 17 Working-age disabling stroke — 1 in 17 Cannabis use disorder — 1 in 16 Stroke — 1 in 15 Parent death/disability — 1 in 14 Severe hearing loss — 1 in 14 Type 2 diabetes — 1 in 13 Appendicitis — 1 in 13 Untreated depression — 1 in 13 Untreated back pain disability — 1 in 13 Heart disease — 1 in 12 Medical error death — 1 in 12 Compulsive sexual behavior — 1 in 12 Eating disorder — 1 in 11 Hip replacement — 1 in 11 Kidney stones — 1 in 11 Sedentary lifestyle — 1 in 11 Salon infection — 1 in 11 Ovarian cancer — 1 in 91 Colorectal cancer — 1 in 77 Breast cancer — 1 in 59 Liver cancer — 1 in 59 Lung cancer — 1 in 56 Prostate cancer — 1 in 50 Melanoma (UV) — 1 in 29 Low-fiber CRC risk — 1 in 23 Red meat & CRC — 1 in 21 Charred meat & cancer — 1 in 20 Maintenance crash — 1 in 83 Driving on sedating meds — 1 in 77 Texting + driving — 1 in 56 Driving after cannabis — 1 in 53 Eating while driving — 1 in 53 Unbelted crash death — 1 in 53 Speeding 20% over limit — 1 in 48 Motorcycle no helmet — 1 in 45 Spaceflight (astronaut) — 1 in 42 Video watching + driving — 1 in 32 Drowsy driving — 1 in 26 E-scooter injury — 1 in 26 Cruise ship norovirus — 1 in 24 Driving at 0.10% BAC — 1 in 16 Catalytic converter theft — 1 in 83 Pickpocketed while traveling — 1 in 38 Stabbed in an assault — 1 in 37 Vehicle theft — 1 in 34 Street robbery / mugging — 1 in 26 Wrongful conviction — 1 in 24 Drink spiking — 1 in 17 Protest under autocracy — 1 in 12 AMOC collapse — 1 in 20 Sting anaphylaxis — 1 in 50 Cat collar injury — 1 in 25 Fish bone injury — 1 in 68 Restaurant food poisoning — 1 in 58 Vegetarian deficiency — 1 in 25 Intimate deepfake — 1 in 25 Social media problematic use — 1 in 13 Infant fall — 1 in 100 Childbirth death (SSA) — 1 in 55 Co-sleeping death — 1 in 43 Toddler stair fall — 1 in 37 Play swing & slide injury — 1 in 33 Autism diagnosis — 1 in 31 C-section complications — 1 in 29 Toy injury requiring ER (child) — 1 in 21 Preeclampsia — 1 in 20 Severe birth tearing — 1 in 17 Gestational diabetes — 1 in 13 Child fall head injury — 1 in 12 Sports betting financial ruin — 1 in 100 Fighter pilot death — 1 in 48 Commercial fishing career death — 1 in 45 Logging career death — 1 in 34 Dying without heir — 1 in 33 Medical bankruptcy — 1 in 25 Compulsive buying disorder — 1 in 20 Rental listing scam loss — 1 in 20 Mortgage foreclosure — 1 in 14 Musculoskeletal LTD claim — 1 in 14 Day-trading losses — 1 in 13 Extremist govt catastrophe — 1 in 13 Hurricane home destruction — 1 in 17 LASIK complications — 1 in 1,000 Infant pool submersion — 1 in 800 MS — 1 in 769 Workplace fatality — 1 in 690 Typhoid fever — 1 in 654 Unsafe imported products — 1 in 565 Brain aneurysm — 1 in 400 COVID-19 — 1 in 400 Fireworks injury — 1 in 385 Sickle cell disease — 1 in 365 Counterfeit medicine — 1 in 361 Spinal cord injury — 1 in 313 Childhood cancer diagnosis — 1 in 285 Next pandemic death — 1 in 208 Dengue (travel) — 1 in 200 Skipping daily showers — 1 in 200 Not scrubbing feet — 1 in 200 Marrow donation risk — 1 in 167 Schizophrenia — 1 in 143 Accidental fall — 1 in 135 Parkinson's — 1 in 125 Sudden death during exercise — 1 in 123 Suicide (US) — 1 in 121 Opioid addiction — 1 in 114 Tuberculosis (global) — 1 in 108 Radon cancer — 1 in 435 Testicular cancer — 1 in 250 Cervical cancer — 1 in 167 Pancreatic cancer — 1 in 125 Pedestrian death — 1 in 806 Motorcycle crash — 1 in 694 Boating drowning — 1 in 685 Driver kills pedestrian — 1 in 552 Phone-distracted walking injury — 1 in 400 EV battery fire — 1 in 333 Cyclist killed by car — 1 in 196 Hand-held phone call + driving — 1 in 143 Petrol car fire — 1 in 125 Self-driving car fatality — 1 in 115 Car crash — 1 in 105 Firefighter duty death — 1 in 455 Police duty death — 1 in 313 Homicide — 1 in 287 Pig-butchering scam — 1 in 106 Extreme heat — 1 in 333 Climate change death — 1 in 204 Swallowed bee/wasp — 1 in 500 Bat bite & rabies — 1 in 238 Mosquito-borne disease — 1 in 190 Food poisoning (global) — 1 in 317 Solar panel fire — 1 in 667 Untreated childhood scoliosis — 1 in 1,000 Child window fall — 1 in 855 Walker stair fall — 1 in 625 Baby walker injury — 1 in 455 Maternal mortality — 1 in 272 Untreated childhood flat feet — 1 in 250 Maternal age & birth defects — 1 in 200 Child death (<18) — 1 in 143 Caving career death — 1 in 167 EMS duty death — 1 in 794 Civilian war casualty — 1 in 499 Soldier in combat — 1 in 270 Mining career death — 1 in 214 Gambling financial ruin — 1 in 159 Wildfire home destruction — 1 in 120 Lightning home fire — 1 in 105 Malaria (travel) — 1 in 10,000 Infection from shared drink — 1 in 10,000 Chagas disease — 1 in 8,475 Wild berry fox tapeworm — 1 in 8,475 Schistosomiasis death — 1 in 6,667 Sudden death (young adult) — 1 in 3,922 Unsafe wiring — 1 in 3,390 Sepsis from wound — 1 in 2,857 Anesthesia awareness — 1 in 2,500 Heat stroke (outdoor) — 1 in 1,905 House fire — 1 in 1,818 Rabies from dogs — 1 in 1,449 Drowning — 1 in 1,379 Shallow-water diving SCI — 1 in 1,111 Choking — 1 in 1,099 EVALI vaping hospitalization — 1 in 1,064 Betel nut cancer — 1 in 1,290 Blood clot (flight) — 1 in 4,651 Killing a cyclist — 1 in 3,937 Teen road-crash death — 1 in 3,030 Child rear bike seat — 1 in 2,500 Child without restraint — 1 in 2,000 Fatal police encounter — 1 in 4,739 Honor killing — 1 in 2,381 Intimate-partner homicide — 1 in 1,767 Hurricane — 1 in 8,929 Drought famine death — 1 in 6,536 Blizzard death — 1 in 4,367 Earthquake — 1 in 3,802 Dog chocolate death — 1 in 2,000 Food poisoning (US) — 1 in 1,862 Fish mercury — 1 in 1,695 Phone/laptop battery fire — 1 in 1,136 SIDS — 1 in 7,143 Laundry pod ingestion — 1 in 6,494 Untreated infant hip dysplasia — 1 in 5,000 Pool drowning — 1 in 2,299 War (civilian) — 1 in 2,000 Fatal bee/wasp sting — 1 in 76,923 Anesthesia death — 1 in 50,000 Dog hot car death — 1 in 41,667 Anaphylaxis — 1 in 27,548 Chiropractic neck manipulation — 1 in 16,667 CO poisoning — 1 in 14,006 Hepatitis A (travel) — 1 in 12,500 Skipping allergy immunotherapy — 1 in 11,111 Acrylamide & cancer — 1 in 16,667 Bus crash — 1 in 100,000 Plane crash — 1 in 58,824 Child pedestrian (residential) — 1 in 45,455 Railroad crossing death — 1 in 20,704 Child bike trailer — 1 in 14,286 Acid attack — 1 in 89,286 Terrorism — 1 in 77,519 Child stranger abduction — 1 in 38,760 Stranger kidnapping — 1 in 35,211 Dowry death — 1 in 13,158 Accidental gun death — 1 in 11,299 Wildfire — 1 in 100,000 Tornado — 1 in 80,645 Tsunami — 1 in 52,632 Ocean drowning — 1 in 29,155 Flood — 1 in 20,202 Landslide death — 1 in 18,416 Supervolcano eruption — 1 in 12,376 Crocodile attack — 1 in 84,746 Bee sting — 1 in 78,927 Fatal scorpion sting — 1 in 26,110 Plastic container leaching — 1 in 16,949 Infant in car seat — 1 in 64,935 Bouncer chair fall — 1 in 60,606 Toddler choking — 1 in 50,000 Unsupervised infant choking — 1 in 50,000 Magnet ingestion — 1 in 12,048 Snorkeling death — 1 in 21,739 Pet in transport — 1 in 20,000 Landmine or UXO injury — 1 in 14,728 Vaccine reaction — 1 in 763,359 Aluminum & Alzheimer's — 1 in 169,492 Residential gas leak — 1 in 140,845 Child hot car death — 1 in 102,041 Glyphosate & cancer — 1 in 1,000,000 Teflon cookware cancer — 1 in 169,492 Roller coaster injury — 1 in 312,500 Cruise ship accident — 1 in 188,679 Ferry sinking — 1 in 133,333 Turbulence injury — 1 in 114,943 School shooting — 1 in 192,308 Mass shooting — 1 in 113,636 Nuclear accident — 1 in 833,333 Avalanche — 1 in 210,526 Lightning — 1 in 209,205 Snake bite — 1 in 884,956 Spider bite — 1 in 833,333 Hippo attack — 1 in 564,972 Dog bite — 1 in 142,045 Pesticide residue — 1 in 1,000,000 Dirty can illness — 1 in 200,000 PLA bioplastic harm — 1 in 169,492 Charger left plugged in — 1 in 200,000 Infant swing death — 1 in 714,286 Child blind cord strangulation — 1 in 416,667 Child plastic bag suffocation — 1 in 263,158 Button battery — 1 in 250,000 Inclined sleeper death — 1 in 238,095 Elevator/escalator death — 1 in 188,324 Japanese encephalitis (travel) — 1 in 2,000,000 Kid + front airbag — 1 in 10,000,000 Asteroid impact — 1 in 1,351,351 Banana spider eggs — 1 in 10,000,000 Shark attack — 1 in 5,681,818 Bear attack — 1 in 3,787,879 Wild berry poisoning — 1 in 2,222,222 Space debris hits property — 1 in 10,000,000 Piranha attack — 1 in 135,135,135 Phone at gas pump — 1 in 1,000,000,000 Phone on plane — 1 in 1,000,000,000 Alien contact — 1 in 169,491,525
Lottery jackpot 1 in 95,238